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Characteristics of Particulate Pollution (PM 2.5 and PM 10 ) and Their Spacescale-Dependent Relationships with Meteorological Elements in China

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  • Xiaodong Li

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

  • Xuwu Chen

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

  • Xingzhong Yuan

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

  • Guangming Zeng

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

  • Tomás León

    (School of Public Health, University of California, Berkeley, CA 94720, USA)

  • Jie Liang

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

  • Gaojie Chen

    (College of Mathematics and Econometrics, Hunan University, Changsha 410082, China)

  • Xinliang Yuan

    (College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
    Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, China)

Abstract

Particulate matter (PM) pollution in China has an obvious characteristic of spatial distribution. It is well known that intensive anthropogenic activities, such as fossil fuel combustion and biomass burning, have great influence on the spatial distribution of PM pollution. However, the spacescale-dependent relationships between PM concentrations and weather conditions remain unclear. Here, we investigated the characteristics of two types of particulate pollution, including PM 2.5 and PM 10 , and their spatial relationships with meteorological elements in 173 cities throughout China from March 2014 to February 2015. Results: (1) High PM 2.5 concentrations were distinctly located southeast of the Hu Line, and high PM 10 concentrations were distinctly situated north of the Yangtze River; (2) Spacescale-dependent relationships were found between PM pollution and meteorological elements. The influence of temperature had similar inverted V-shaped characteristics, namely, there was serious PM pollution when temperature was about 15 °C, and there was slight PM pollution when temperature was less or more than 15 °C. Annual precipitation, wind speed, and relative humidity were negatively correlated with PM, while annual atmospheric pressure was positively correlated with PM; (3) The ideal meteorological regions were identified according to the quantified spatial relationships between PM and meteorological elements, which could be defined by a combination of the following conditions: (a) temperature <10 °C or >21 °C; (b) precipitation >1500 mm; (c) atmospheric pressure <900 hPa; (d) wind speed >3 m/s; and (e) relative humidity >65%, where air pollutants can easily be scavenged. The success of this research provides a meteorological explanation to the spatial distribution characteristics of PM pollution in China.

Suggested Citation

  • Xiaodong Li & Xuwu Chen & Xingzhong Yuan & Guangming Zeng & Tomás León & Jie Liang & Gaojie Chen & Xinliang Yuan, 2017. "Characteristics of Particulate Pollution (PM 2.5 and PM 10 ) and Their Spacescale-Dependent Relationships with Meteorological Elements in China," Sustainability, MDPI, vol. 9(12), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2330-:d:122883
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    References listed on IDEAS

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    4. Jianhui Xu & Hong Jiang & Zhongyong Xiao & Bin Wang & Jian Wu & Xin Lv, 2016. "Estimating Air Particulate Matter Using MODIS Data and Analyzing Its Spatial and Temporal Pattern over the Yangtze Delta Region," Sustainability, MDPI, vol. 8(9), pages 1-14, September.
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    1. Danyang Guo & Jilai Yu & Mingfei Ban, 2018. "Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    2. Xiangxue Zhang & Changxiu Cheng, 2022. "Temporal and Spatial Heterogeneity of PM 2.5 Related to Meteorological and Socioeconomic Factors across China during 2000–2018," IJERPH, MDPI, vol. 19(2), pages 1-15, January.
    3. Wissanupong Kliengchuay & Aronrag Cooper Meeyai & Suwalee Worakhunpiset & Kraichat Tantrakarnapa, 2018. "Relationships between Meteorological Parameters and Particulate Matter in Mae Hong Son Province, Thailand," IJERPH, MDPI, vol. 15(12), pages 1-13, December.
    4. Binxu Zhai & Jianguo Chen & Wenwen Yin & Zhongliang Huang, 2018. "Relevance Analysis on the Variety Characteristics of PM 2.5 Concentrations in Beijing, China," Sustainability, MDPI, vol. 10(9), pages 1-15, September.

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